FINAL: NSH 6 — BOS 3. Our Monte Carlo simulation projected NSH 2.44 - BOS 3.82 (BOS at 56.0% win probability). The spread is -1.5 and the total is 6.5.
NSH
2.44
Projected Score
VS
O/U 6.5
BOS
3.82
Projected Score
Win Probability
NSHBOS
-1.5
Spread (NSH)
6.5
Total Line
1,000
Simulations
Calibrated accuracy at this confidence: 48.7% (1,083 games)
Projected Goals Range 10th – 90th percentile
BOS
2.73.84.9
NSH
1.42.43.5
Projected
NSH 2.44 — BOS 3.82
Actual
NSH 6 — BOS 3
Pick Results
Under 6.0totalLOSS-1.00u
Game Odds
NSH ML
-118
BOS ML
-104
Puck Line
-1.5
Total
6.5
Edge Detail
NSH Edge
-10.1%
BOS Edge
+5.0%
Projected Total
6.27
-0.23 vs line
Goalie Matchup
Jeremy Swayman
22-292.86 GAA90.4% SV
Juuse Saros
20-313.19 GAA89.2% SV
Special Teams
Power Play
Penalty Kill
90% Confidence: 37.4% – 50.6% home win probability
AI Intelligence Analysis
LEANYELLOW ZONE48.8% WR (n=80)
BOS (34-21-5, .608 pt%) is the clearly superior team over NSH (27-26-8, .508 pt%) and is correctly priced as road favorites, but Swayman's struggles (.892 SV%, backup tier) and NSH's surprisingly adequate Saros (.896) narrow the gap.
Key Factors
- BOS record: 34-21-5 (.608) vs NSH 27-26-8 (.508) — BOS clear quality advantage (~10 points in standings)
- BOS goalie Swayman: .892 SV%, 3.11 GAA — classified as backup tier, concerning for an away road favorite
- NSH goalie Saros: .896 SV%, 2.98 GAA — also backup tier, but home with 3-in-4 schedule flag for NSH
- NSH form: 1-4 L5, 3-7 L10 (COLD); BOS form: 2-3 L5, 6-4 L10 — BOS better but neither hot
- Away ML in 5-10% edge range: YELLOW 48.8% WR — structurally neutral for BOS road chalk
Risk Factors
- Our recent pick BOS ML on 2/28 vs PHI was a LOSS (-1.5u) — recent track record negative on BOS ML
- BOS Swayman .892 SV% is below average — backup tier on road against NSH home crowd
- NSH is 3-in-4 schedule flag but only 2 days rest — not a meaningful fatigue edge
GOALIE UNCONFIRMEDCOLD STREAK
Edge Analysis
Moneyline
BOS 56.0%
-10.1 pts
Spread
-1.5
-10.1 pts
Total
6.5
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How this prediction was generated: This page shows output from the Olympus Bets NHL Hockey Monte Carlo engine. Each game is simulated 1,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →